5  motivation

5.1 Jerusalem, 2019

Data from the Israel Meteorological Service, IMS.

The temperature fluctuates in various time scales, from daily to yearly. Let’s think together a few questions we’d like to ask about the data above.

Now let’s see precipitation data:

Again, what kind of questions come to mind?

We have not talked about what kind of data we have in our hands here. The csv file provided by the IMS looks like this:

Station Date & Time (Winter) Diffused radiation (W/m^2) Global radiation (W/m^2) Direct radiation (W/m^2) Relative humidity (%) Temperature (°C) Maximum temperature (°C) Minimum temperature (°C) Wind direction (°) Gust wind direction (°) Wind speed (m/s) Maximum 1 minute wind speed (m/s) Maximum 10 minutes wind speed (m/s) Time ending maximum 10 minutes wind speed (hhmm) Gust wind speed (m/s) Standard deviation wind direction (°) Rainfall (mm)
0 Jerusalem Givat Ram 01/01/2019 00:00 0.0 0.0 0.0 80.0 8.7 8.8 8.6 75.0 84.0 3.3 4.3 3.5 23:58 6.0 15.6 0.0
1 Jerusalem Givat Ram 01/01/2019 00:10 0.0 0.0 0.0 79.0 8.7 8.8 8.7 74.0 82.0 3.3 4.1 3.3 00:01 4.9 14.3 0.0
2 Jerusalem Givat Ram 01/01/2019 00:20 0.0 0.0 0.0 79.0 8.7 8.8 8.7 76.0 82.0 3.2 4.1 3.3 00:19 4.9 9.9 0.0
3 Jerusalem Givat Ram 01/01/2019 00:30 0.0 0.0 0.0 79.0 8.7 8.7 8.6 78.0 73.0 3.6 4.2 3.6 00:30 5.2 11.7 0.0
4 Jerusalem Givat Ram 01/01/2019 00:40 0.0 0.0 0.0 79.0 8.6 8.7 8.5 80.0 74.0 3.6 4.4 3.8 00:35 5.4 10.5 0.0
... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...
52549 Jerusalem Givat Ram 31/12/2019 22:20 0.0 0.0 1.0 81.0 7.4 7.6 7.3 222.0 255.0 0.5 0.9 1.0 22:11 1.0 47.9 0.0
52550 Jerusalem Givat Ram 31/12/2019 22:30 0.0 0.0 1.0 83.0 7.3 7.4 7.3 266.0 259.0 0.6 0.8 0.6 22:28 1.1 22.8 0.0
52551 Jerusalem Givat Ram 31/12/2019 22:40 0.0 0.0 1.0 83.0 7.5 7.6 7.3 331.0 317.0 0.5 0.8 0.6 22:35 1.0 31.6 0.0
52552 Jerusalem Givat Ram 31/12/2019 22:50 0.0 0.0 1.0 83.0 7.5 7.6 7.4 312.0 285.0 0.6 1.0 0.6 22:50 1.4 31.3 0.0
52553 Jerusalem Givat Ram 31/12/2019 23:00 0.0 0.0 1.0 83.0 7.6 7.7 7.4 315.0 321.0 0.7 1.0 0.8 22:54 1.3 23.5 0.0

52554 rows × 18 columns

We see that we have data points spaced out evenly every 10 minutes.

5.2 Monthly summaries

Let’s try to answer the following questions:

First we have to divide temperature data by month, and then take the average for each month.

This is a bit trickier.

  1. We need to find the maximum/minimum temperature for each day.
  2. Only then we split the daily data by month and take the average.

We have to divide rain data by month, and then sum the totals of each month.

  1. We need to sum rain by day.
  2. We need to count how many days are there each month where rain > 0.